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The purpose of this article is to evaluate performance of minimum energy controllers thoroughly on a tiltrotor aircraft.

Minimum energy controllers are designed for tiltrotor aircraft models for helicopter and airplane modes. Performance of minimum energy controllers is evaluated with respect to several criteria.

Minimum energy controllers can be used for tiltrotor aircraft flight control system design. These controllers show satisfactory performance when noise intensities and variance bounds vary.

Minimum energy controllers can be implemented for tiltrotor aircraft flight control system design.

In this paper, minimum energy controllers are applied for tiltrotor aircraft flight control system design and the performance of minimum energy controllers is evaluated deeply on a complex physical system (i.e. tiltrotor aircraft).

This paper aims to present novel results for trajectory tracking of tandem-rotor helicopters via variance-constrained controllers.

Regarding these purposes, linearized tandem-rotor helicopter models are benefitted.

Variance-constrained controllers are very beneficial for trajectory tracking of tandem-rotor helicopters while there exists variance bounds on outputs of interest.

Variance-constrained controllers can be used for cheaper tandem-rotor helicopter operations with high trajectory tracking quality.

Applying variance-constrained control strategy for tandem-rotor helicopters during trajectory tracking. This also causes less fuel consumption and green environment, and good trajectory tracking quality.

Are share markets too volatile? While it is difficult to ignore share market volatility it is important to determine whether volatility is excessive. This paper replicates the Shiller (1981) test as well as applying standard time series analysis to annual Australian stock market data for the period 1883 to 1999. While Shiller’s test suggests the possibility of excess volatility, time series analysis identifies a long‐run relationship between share market value and dividends, consistent with the share market reverting to its fundamental discounted cash flow value over time.

The nature and extent of our knowledge of stock market efficiency are examined. The development of “efficiency”, as a way of thinking about stock markets, is traced from Roberts (1959) and Fama (1965) onward. The early work successfully introduced competitive economic theory to the study of stock markets and paved the way for a flood of empirical research on the relation between information and stock prices. This literature irreversibly altered our views on stock market behavior. The theory and evidence of seemingly‐rational use of information lay in sharp contrast to prior beliefs. It was associated with a widespread increase in respect for stock markets, financial markets, and markets in general, at the time. Researchers began developing and using a variety of formal models of security prices. Nevertheless, “efficiency” has its limitations, both theoretically (as a way of characterizing markets) and empirically (by stretching the quality of the data, the estimation techniques used, and our knowledge of price behavior in competitive markets). Extensive evidence of anomalies suggests either that the market systematically misprices securities or that the theoretical or empirical limitations are binding, or both. The less interesting research question now is whether markets are efficient, and the more interesting question is how we can learn more about price and transactions behavior in competitive stock markets. The concept of an “efficient stock market” has stimulated both insight and controversy since Fama (1965) introduced it to the financial economics literature. As a construct, “efficiency” models the stock market in terms of the reaction of prices to the flow of information. Like all theory choices, modelling the market in this fashion involved tradeoffs. The benefits included opening the literature to an abundance of high‐quality researchable data, covering a variety of information, and the resulting insights obtained on the role of information in setting prices. The opportunity costs included temporarily closing the literature to alternative ways of viewing stock markets, for example by modelling public information as a homogenous good and thus ignoring factors such as differences in beliefs among investors, differences in information processing costs, and the “animal spirits” that might drive group behavior. The costs also included reliance on particular asset‐pricing models of how an “efficient” market would set prices. Not surprisingly, the ensuing deluge of research has produced some startling evidence, for and against the proposition that financial markets are “efficient”. Strongly‐conflicting views and puzzling anomalies remain. The early evidence seemed unexpectedly consistent with the theory. The theory, and its implications, also seemed clear at the time. After a period that seems short in retrospect, the growing body of evidence in favor of the efficient market hypothesis emerged as one of the most influential empirical areas of economics. Fama's (1970) review described a flourishing, coherent and confident literature. This research had an irreversible effect on our knowledge of and attitude toward stock markets, and financial markets generally. It coincided with an emergence of interest in, and respect for, all markets among economists and politicians, and influenced the worldwide trend toward “liberalizing” financial and other markets. The research consistently appeared to show an unbiased reaction of stock prices to public information. The property of “unbiased reaction” to public information, which formed the basis of the early definitions of “efficiency”, was seen to be an implication of rational, maximizing investor behavior in competitive securities markets (Fama 1965, p.4). Reduced to a basic level, the reasoning was that any systematicallybiased reaction to public information is costlessly publicly observable, and thus provides pure profit opportunities to be competed away. Characterizing the market in terms of its reaction to information is only one of many feasible ways of modelling stock price behavior, but it introduced economic theoryto the empirical studyof stock prices, which had received little serious attention from economists prior to that point. Despite the subsequent spate of anomalies, the early efficiency literature not only adapted standard economic theoryto provide the first formal economic insights into how stock prices behave, but it helped pave the way for an outporing of theoretical and empirical work on stock markets and capital markets in general. Subsequent empirical research was not as consistent with the theory. Evidence of “anomalous” return behavior now is widespread and well‐known. It generallytakes the form of variables (for example, size, day‐of‐the‐week, P/E ratio, market/book value ratio, rank of scaled earnings change, dividend yield) that are significantly but inexplicablyrelated to subsequent abnormal stock returns. Much of this evidence has defied rational economic explanation to date and appears to have caused many researchers to strongly qualify their views on market efficiency. Disagreement has not been not confined to the evidence. The literature has produced a variety of research designs, ranging from the “market model” of Fama, Fisher, Jensen and Roll (FFJR, 1969) to Shiller's (1981a,b) variance‐bounds tests. The very term “efficiency” has engendered controversy: there is a modest literature on precisely what efficiency means, on the role of transaction costs, and on whether efficient markets are logically feasible. Making sense of this literature requires careful definition of “efficiency” in this context and careful analysis of the type of evidence that has been offered in relation to it. This involves an assessment of the strengths and weaknesses of both the theory of efficient markets, as a way of characterizing stock markets, and of the data and research designs used in testing it. Not surprisingly, a mixed conclusion emerges. While the concept of efficient markets was an audacious departure from the comparative ignorance and suspicion among economists of stock markets that preceded it, and provides valuable insights into their behavior, the concept has its limitations, in terms of both its internal logical coherence and its fit with the data. Section 1 ofthis survey sketches the development of the efficient market theory, reviewing the principal contributions in terms of their usefulness in guiding and evaluating empirical research. Section 2 addresses the limitations inherent in what is knowable about stock market efficiency, given the present state of theory about how security prices might behave in an “efficient” market. It argues that there are binding limitations in the theoryof asset pricing, some of which are known and others of which are unknown or even unknowable. These limitations must be borne in mind when choosing whether to interpret the data as evidence of: (1) market efficiency, under the maintained hypothesis that a specific research design, including a specific model of asset pricing used to benchmark price behavior, correctly describes pricing in an efficient market; or (2) the ability of our models and research designs to encapsulate how prices behave in an efficient market, under the maintained hypothesis of efficiency. Against this background, section 3 then provides an assessment of the accomplishments of the theory of stock market efficiency, including an interpretation of the evidence. It focuses on the nature and influence of the evidence and does not attempt to provide a comprehensive literature taxonomy. The final section offers conclusions. The principal conclusion is that the theory of efficient markets has irreversibly enhanced our knowledge of and respect for stock markets (and perhaps for all financial market or even for markets in general) but that, like all theories, it is fundamentally flawed.

In this paper, we study partial identification of the distribution of treatment effects of a binary treatment for ideal randomized experiments, ideal randomized experiments with a known value of a dependence measure, and for data satisfying the selection-on-observables assumption, respectively. For ideal randomized experiments, (i) we propose nonparametric estimators of the sharp bounds on the distribution of treatment effects and construct asymptotically valid confidence sets for the distribution of treatment effects; (ii) we propose bias-corrected estimators of the sharp bounds on the distribution of treatment effects; and (iii) we investigate finite sample performances of the proposed confidence sets and the bias-corrected estimators via simulation.

In reliability studies, interests in discrete failure data came relatively late in comparison to its continuous analogue. Also, discrete failure data arise in several common situations. So, in this paper the authors try to study some reliability concepts such as reversed variance and reversed mean residual life functions based on discrete lifetime random variable.

Supposed T be a non‐negative discrete random variable, then based on reversed residual random variable T_k^*=(k−T|T≤k), some useful and applicable relations and bounds are achieved.

In this paper, the authors study the reversed variance residual life in discrete lifetime distributions, the results of which are not similar to the continuous case. Its relationship with reversed mean residual life and reversed residual coefficient of variation are obtained. Also, its monotonicity and the associated ageing classes of distributions are discussed. Some characterization results of the class of increasing reversed variance residual life, which is denoted by IRVR, are presented and the upper bound for reversed variance residual life under some conditions is obtained.

There are many situations where a continuous time is inappropriate for describing the lifetime of devices and other systems. For example, the lifetime of many devices in industry, such as switches and mechanical tools, depends essentially on the number of times that they are turned on and off or the number of shocks they receive. In such cases, the time to failure is often more appropriately represented by the number of times they are used before they fail, which is a discrete random variable.

All the results based on discrete reversed residual lifetime, such as the relationships among reversed mean, variance and coefficient of variation residual lifetime and also their monotonicity ageing classes, are new.

The purpose of this paper is to provide a rigorous, statistically correct, and low‐cost way to audit sample a lender's loan portfolio, be they a microlender or other type of lender. No other paper applies this method to loan portfolios, even though it is a high demand application.

Standard techniques of audit sampling and dollar unit sampling with stratification are applied to the particular case of a microlender's portfolio. Unlike the audit sampling that almost all auditors use, no arbitrary rules of thumb are applied.

The paper finds that statistical audit sampling for a lender's loan portfolio is simple, rigorous, and inexpensive.

In audit sampling, most auditors use arbitrary rules of thumb and have no idea whether they are sampling enough items to actually be sure, with some desired level of confidence, that they have found no defects. This simple, inexpensive, and statistically rigorous technique will allow auditors who actually want to do a good job to quantify the precision of their statements in a very common application.

This paper combines several disparate threads from the statistical literature on audit sampling in a way that auditors (who are usually not statisticians) can apply them for auditing the quality of a lender's portfolio – microfinance or otherwise – which is a very common need.

This paper examines variable selection among various factors related to motor vehicle fatality rates using a rich set of panel data. Four Bayesian methods are used. These include Extreme Bounds Analysis (EBA), Stochastic Search Variable Selection (SSVS), Bayesian Model Averaging (BMA), and Bayesian Additive Regression Trees (BART). The first three of these employ parameter estimation, the last, BART, involves no parameter estimation. Nonetheless, it also has implications for variable selection. The variables examined in the models include traditional motor vehicle and socioeconomic factors along with important policy-related variables. Policy recommendations are suggested with respect to cell phone use, modernization of the fleet, alcohol use, and diminishing suicidal behavior.

This study aims to examine the effects of climate change and agricultural technologies on crop production in Vietnam for the period 1990–2018.

Several econometric techniques – such as the augmented Dickey–Fuller, Phillips–Perron, the autoregressive distributed lag (ARDL) bounds test, variance decomposition method (VDM) and impulse response function (IRF) are used for the empirical analysis.

The results of the ARDL bounds test confirm the significant dynamic relationship among the variables under consideration, with a significance level of 1%. The primary findings indicate that the average annual temperature exerts a negative influence on crop yield, both in the short term and in the long term. The utilization of fertilizer has been found to augment crop productivity, whereas the application of pesticides has demonstrated the potential to raise crop production in the short term. Moreover, both the expansion of cultivated land and the utilization of energy resources have played significant roles in enhancing agricultural output across both in the short term and in the long term. Furthermore, the robustness outcomes also validate the statistical importance of the factors examined in the context of Vietnam.

This study provides persuasive evidence for policymakers to emphasize advancements in intensive agriculture as a means to mitigate the impacts of climate change. In the research, the authors use average annual temperature as a surrogate measure for climate change, while using fertilizer and pesticide usage as surrogate indicators for agricultural technologies. Future research can concentrate on the impact of ICT, climate change (specifically pertaining to maximum temperature, minimum temperature and precipitation), and agricultural technological improvements that have an impact on cereal production.

To the best of the authors’ knowledge, this study is the first to examine how climate change and technology effect crop output in Vietnam from 1990 to 2018. Various econometrics tools, such as ARDL modeling, VDM and IRF, are used for estimation.

This paper aims to perform an analytical analysis on portfolio allocation when a tracking error volatility (TEV) constraint holds, drawing specific attention to the portfolio efficiency issue. Indeed, it is well known that investors can assign part of their funds to asset managers who are given the task of beating a benchmark portfolio. However, the risk management office often imposes a TEV constraint to the asset managers’ activity to maintain the portfolio risk near to the risk of the benchmark. This situation could lead asset managers to select non efficient portfolios in the total return and absolute risk perspective. However, the risk management office can impose further constraints, such as on maximum variance or maximum value at risk (VaR) to maintain the overall portfolio risk under control.

First the authors define the TEV constrained-efficient frontier (ECTF), a set of TEV constrained portfolios that are mean–variance efficient. Second, they define two new portfolio frontiers analyzing how the imposition of a maximum variance or maximum VaR restriction can reduce the ECTF. Third, they investigate the feasibility of such portfolio frontiers and their relationships.

The authors find that variance or VaR constraint can force asset managers to pursue portfolio efficiency.

This is a practically important issue given that asset managers often receive a constraint on TEV from the risk management office, but the risk management office does not ask them to minimize the TEV as often assumed in the optimizations performed in the literature on this topic.